1 to 7 of 7 Results
Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]
This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Sof... |
Aichem, Michael; Klein, Karsten; Kobourov, Stephen; Schreiber, Falk, 2023, "Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations"", https://doi.org/10.18419/darus-3706, DaRUS, V2
This dataset contains the supplemental materials for our publication "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations". The publication reports on an experiment that we conducted to explore the effect... |
Wang, Yao, 2024, "SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3884, DaRUS, V1
Understanding the link between visual attention and user’s needs when visually exploring information visualisations is under-explored due to a lack of large and diverse datasets to facilitate these analyses. To fill this gap, we introduce SalChartQA - a novel crowd-sourced datase... |
Feyer, Stefan Paul; Pinaud, Bruno; Kobourov, Stephen; Brich, Nicolas; Krone, Michael; Kerren, Andreas; Schreiber, Falk; Klein, Karsten, 2023, "Supplemental Material: "2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualizations in Virtual Reality"", https://doi.org/10.18419/darus-3387, DaRUS, V1, UNF:6:PSjD1vZ/FkCWAinPKFoFOg== [fileUNF]
Dataset containing supplemental material for the publication "2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualizations in Virtual Reality" This dataset contains: 1) archive containing all raw quantitative results, 2) archive containing all raw qualitative data,... |
Wang, Yao, 2023, "Data for: "Scanpath Prediction on Information Visualizations"", https://doi.org/10.18419/darus-3361, DaRUS, V2, UNF:6:cqkNueYjBVCLYaXEqJq3yw== [fileUNF]
We propose Unified Model of Saliency and Scanpaths (UMSS) - a model that learns to predict multi-duration saliency and scanpaths (i.e. sequences of eye fixations) on information visualisations. Although scanpaths provide rich information about the importance of different visualis... |
Dec 7, 2022 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Görtler, Jochen; Spinner, Thilo; Weiskopf, Daniel; Deussen, Oliver, 2022, "Replication Data for: Uncertainty-Aware Principal Component Analysis", https://doi.org/10.18419/darus-2321, DaRUS, V1
This dataset contains the source code for uncertainty-aware principal component analysis (UA-PCA) and a series of images that show dimensionality reduction plots created with UA-PCA. The software is a JavaScript library for performing principal component analysis and dimensionali... |
Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/darus-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF]
Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and pre... |
